70-767: Implementing a SQL Data Warehouse - Free download from Exam Hub

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You have a Microsoft Azure SQL Data Warehouse instance that must be available six months a day for reporting.

You need to pause the compute resources when the instance is not being used.

Solution: You use SQL Server Configuration Manager.

Does the solution meet the goal?

Yes
No

Correct answer: B

Explanation:

To pause a SQL Data Warehouse database, use any of these individual methods. Pause compute with Azure portal Pause compute with PowerShell Pause compute with REST APIs References:https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-overview

To pause a SQL Data Warehouse database, use any of these individual methods.

Pause compute with Azure portal

Pause compute with PowerShell

Pause compute with REST APIs

References:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-overview

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have a Microsoft Azure SQL Data Warehouse instance that must be available six months a day for reporting.

You need to pause the compute resources when the instance is not being used.

Solution: You use the Azure portal.

Does the solution meet the goal?

Yes
No

Correct answer: A

Explanation:

To pause a SQL Data Warehouse database, use any of these individual methods. Pause compute with Azure portal Pause compute with PowerShell Pause compute with REST APIs Note: To pause a database:1. Open the Azure portal and open your database. Notice that the Status is Online. 2. To suspend compute and memory resources, click Pause, and then a confirmation message appears. Click yes to confirm or no to cancel. References:https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-overviewhttps://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-portal#pause-compute-bk

To pause a SQL Data Warehouse database, use any of these individual methods.

Pause compute with Azure portal

Pause compute with PowerShell

Pause compute with REST APIs

Note: To pause a database:

1. Open the Azure portal and open your database. Notice that the Status is Online.

2. To suspend compute and memory resources, click Pause, and then a confirmation message appears. Click yes to confirm or no to cancel.

References:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-overview

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-portal#pause-compute-bk

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have a Microsoft Azure SQL Data Warehouse instance that must be available six months a day for reporting.

You need to pause the compute resources when the instance is not being used.

Solution: You use SQL Server Management Studio (SSMS).

Does the solution meet the goal?

Yes
No

Correct answer: B

Explanation:

To pause a SQL Data Warehouse database, use any of these individual methods. Pause compute with Azure portal Pause compute with PowerShell Pause compute with REST APIs References:https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-overview

To pause a SQL Data Warehouse database, use any of these individual methods.

Pause compute with Azure portal

Pause compute with PowerShell

Pause compute with REST APIs

References:

https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-manage-compute-overview

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have a data warehouse that stores information about products, sales, and orders for a manufacturing company. The instance contains a database that has two tables named SalesOrderHeader and SalesOrderDetail. SalesOrderHeader has 500,000 rows and SalesOrderDetail has 3,000,000 rows.

Users report performance degradation when they run the following stored procedure:

You need to optimize performance.

Solution: You run the following Transact-SQL statement:

Does the solution meet the goal?

Yes
No

Correct answer: B

Explanation:

100 out of 500,000 rows is a too small sample size. References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics

100 out of 500,000 rows is a too small sample size.

References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics

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You have a data warehouse that stores information about products, sales, and orders for a manufacturing company. The instance contains a database that has two tables named SalesOrderHeader and SalesOrderDetail. SalesOrderHeader has 500,000 rows and SalesOrderDetail has 3,000,000 rows.

Users report performance degradation when they run the following stored procedure:

You need to optimize performance.

Solution: You run the following Transact-SQL statement:

Does the solution meet the goal?

Yes
No

Correct answer: A

Explanation:

You can specify the sample size as a percent. A 5% statistics sample size would be helpful. References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics

You can specify the sample size as a percent. A 5% statistics sample size would be helpful.

References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-statistics

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have the following line-of-business solutions:

ERP system
Online WebStore
Partner extranet

One or more Microsoft SQL Server instances support each solution. Each solution has its own product catalog. You have an additional server that hosts SQL Server Integration Services (SSIS) and a data warehouse. You populate the data warehouse with data from each of the line-of-business solutions. The data warehouse does not store primary key values from the individual source tables.

The database for each solution has a table named Products that stored product information. The Products table in each database uses a separate and unique key for product records. Each table shares a column named ReferenceNr between the databases. This column is used to create queries that involve more than once solution.

You need to load data from the individual solutions into the data warehouse nightly. The following requirements must be met:

If a change is made to the ReferenceNr column in any of the sources, set the value of IsDisabled to True and create a new row in the Products table.
If a row is deleted in any of the sources, set the value of IsDisabled to True in the data warehouse.

Solution: Perform the following actions:

Enable the Change Tracking feature for the Products table in the three source databases.
Query the CHANGETABLE function from the sources for the deleted rows.
Set the IsDIsabled column to True on the data warehouse Products table for the listed rows.

Does the solution meet the goal?

Yes
No

Correct answer: B

Explanation:

We must check for updated rows, not just deleted rows. References: https://www.timmitchell.net/post/2016/01/18/getting-started-with-change-tracking-in-sql-server/

We must check for updated rows, not just deleted rows.

References: https://www.timmitchell.net/post/2016/01/18/getting-started-with-change-tracking-in-sql-server/

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You are developing a Microsoft SQL Server Integration Services (SSIS) projects. The project consists of several packages that load data warehouse tables.

You need to extend the control flow design for each package to use the following control flow while minimizing development efforts and maintenance:

Solution: You add the control flow to an ASP.NET assembly. You add a script task that references this assembly to each data warehouse load package.

Does the solution meet the goal?

Yes
No

Correct answer: B

Explanation:

A package consists of a control flow and, optionally, one or more data flows. You create the control flow in a package by using the Control Flow tab in SSIS Designer. References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow

A package consists of a control flow and, optionally, one or more data flows. You create the control flow in a package by using the Control Flow tab in SSIS Designer.

References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You are developing a Microsoft SQL Server Integration Services (SSIS) projects. The project consists of several packages that load data warehouse tables.

You need to extend the control flow design for each package to use the following control flow while minimizing development efforts and maintenance:

Solution: You add the control flow to a control flow package part. You add an instance of the control flow package part to each data warehouse load package.

Does the solution meet the goal?

Yes
No

Correct answer: A

Explanation:

A package consists of a control flow and, optionally, one or more data flows. You create the control flow in a package by using the Control Flow tab in SSIS Designer. References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow

A package consists of a control flow and, optionally, one or more data flows. You create the control flow in a package by using the Control Flow tab in SSIS Designer.

References: https://docs.microsoft.com/en-us/sql/integration-services/control-flow/control-flow

Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.

You have a Microsoft SQL Server data warehouse instance that supports several client applications.

The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it to daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.

All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.

You have the following requirements:

Implement table partitioning to improve the manageability of the data warehouse and to avoid the need to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.
Partition the Fact.Order table and retain a total of seven years of data.
Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest month of data is archived and removed.
Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.
Incrementally load all tables in the database and ensure that all incremental changes are processed.
Maximize the performance during the data loading process for the Fact.Order partition.
Ensure that historical data remains online and available for querying.
Reduce ongoing storage costs while maintaining query performance for current data.

You are not permitted to make changes to the client applications.

You need to optimize the storage for the data warehouse.

What change should you make?

Partition the Fact.Order table, and move historical data to new filegroups on lower-cost storage.
Create new tables on lower-cost storage, move the historical data to the new tables, and then shrink the database.
Remove the historical data from the database to leave available space for new data.
Move historical data to new tables on lower-cost storage.
Implement row compression for the Fact.Order table.
Move the index for the Fact.Order table to lower-cost storage.

Correct answer: A

Explanation:

Create the load staging table in the same filegroup as the partition you are loading. Create the unload staging table in the same filegroup as the partition you are deleting. From scenario: The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.References: https://blogs.msdn.microsoft.com/sqlcat/2013/09/16/top-10-best-practices-for-building-a-large-scale-relational-data-warehouse/

Create the load staging table in the same filegroup as the partition you are loading.

Create the unload staging table in the same filegroup as the partition you are deleting.

From scenario: The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.

References: https://blogs.msdn.microsoft.com/sqlcat/2013/09/16/top-10-best-practices-for-building-a-large-scale-relational-data-warehouse/

Note: This question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other questions in this series. Information and details provided in a question apply only to that question.

You are a database administrator for an e-commerce company that runs an online store. The company has the databases described in the following table.

Each day, you publish a Microsoft Excel workbook that contains a list of product names and current prices to an external website. Suppliers update pricing information in the workbook. Each supplier saves the workbook with a unique name.

Each night, the Products table is deleted and refreshed from MDS by using a Microsoft SQL Server Integration Services (SSIS) package. All files must be loaded in sequence.

You need to add a data flow in an SSIS package to perform the Excel files import in the data warehouse.

What should you use?

Lookup transformation
Merge transformation
Merge Join transformation
MERGE statement
Union All transformation
Balanced Data Distributor transformation
Sequential container
Foreach Loop container

Correct answer: A

Explanation:

If you're familiar with SSIS and don't want to run the SQL Server Import and Export Wizard, create an SSIS package that uses the Excel Source and the SQL Server Destination in the data flow. References: https://docs.microsoft.com/en-us/sql/integration-services/import-export-data/import-data-from-excel-to-sql

If you're familiar with SSIS and don't want to run the SQL Server Import and Export Wizard, create an SSIS package that uses the Excel Source and the SQL Server Destination in the data flow.